Design of a handheld and portable fluorescence imaging system for quantitative detection of pregnancy-specific biomarkers in cattle.

Reproductive management significantly impacts dairy farm productivity, necessitating accurate timely pregnancy detection in cattle. This paper presents a novel handheld and portable fluorescence imaging system designed for quantitative assessment of pregnancy-specific biomarkers, addressing the limitations of current detection methods. The objective was to develop a cost-effective, at-farm solution for detecting pregnancy-specific protein B (PSPB) in bovine plasma samples. The system integrates an imaging module and a custom software application, enabling image capture, data processing, and PSPB concentration determination. Calibration utilizing known PSPB concentrations achieved a 0.6 ng/mL limit of detection. Validation encompassed a comparison with a standard ELISA method using 100 bovine plasma samples; minimal bias and good agreement were observed within the linear range of the calibration curve for both methods. The system offers portability, user-friendliness, and potential for multiplex detection, promising real-time, at-farm reproductive management. This study demonstrates the successful development and validation of a portable fluorescence imaging system, offering an efficient and accurate approach to detecting pregnancy-specific biomarkers in cattle. Its implications extend to improving dairy farm productivity by enabling timely and reliable reproductive management practices.

SmartOCT: smartphone-integrated optical coherence tomography.

Smartphone devices have seen unprecedented technical innovation in computational power and optical imaging capabilities, making them potentially invaluable tools in scientific imaging applications. The smartphone's compact form-factor and broad accessibility has motivated researchers to develop smartphone-integrated imaging systems for a wide array of applications. Optical coherence tomography (OCT) is one such technique that could benefit from smartphone-integration. Here, we demonstrate smartOCT, a smartphone-integrated OCT system that leverages built-in components of a smartphone for detection, processing and display of OCT data. SmartOCT uses a broadband visible-light source and line-field OCT design that enables snapshot 2D cross-sectional imaging. Furthermore, we describe methods for processing smartphone data acquired in a RAW data format for scientific applications that improves the quality of OCT images. The results presented here demonstrate the potential of smartphone-integrated OCT systems for low-resource environments.

Effect of camera distance and angle on color of diverse skin tone-based standards in smartphone photos.

Accurate and reproducible color capture is vital in medical photography. Camera distance and angle are particularly important as they are highly variable in a clinical setting. To account for variability in illumination, camera technology, and geometric effects, color standards are often used for color correction. To explore how geometry affects color, we quantified the change in CIELAB color value of a color standard for diverse skin tones at varying smartphone camera distances and angles. Whereas both chromaticity (a* and b*) and lightness (L*) were affected by angle, distance only affected L* (standard error of measurement, SEM > 1 CIELAB unit). Flash usage did not generally reduce distance and angle associated variability. Compared to compressed (JPG) format, raw (DNG) images had decreased median variability across different distances and angles. These findings suggest that in medical photography, inconsistent camera distance and angle can increase variability in photographed skin appearance over time.

A multi-channel smartphone-based spectroscopic system for high-throughput biosensing in low-resource settings.

Primary healthcare centers (PHC) are the first point of contact for people in low-resource settings, and laboratory services play a critical role in early diagnosis of any disease. In recent years, several smartphone-based spectroscopic systems have been demonstrated to translate lab-confined healthcare applications into point-of-care environments to improve their accessibility. Due to constraints, such as the low availability of skilled personnel and consumables in a PHC, batch processing would be ideal for a large number of samples. Therefore, high-throughput and multi-channel detection is equally critical as affordability and portability. To date, most point-of-care systems are designed to perform a single type of analysis at a time. Herein, we introduce a smartphone-based spectroscopic system based on the use of line-beam illumination to achieve high-throughput sensing (15 channels simultaneously) within a 3d-printed microfluidic device. We also developed a smartphone application to process the spectral data and provide the results in real-time. Bland-Altman analysis revealed that the proposed device performs similarly to a laboratory spectrophotometer. The availability of the developed system will enable detection of multiple samples rapidly in low-resource settings with the existing limited manpower and infrastructures. The fast turnaround time may eventually help in timely diagnosis of patients during situations of high sample load, such as during disease outbreaks.

Recurrence monitoring for ovarian cancer using a cell phone-integrated paper device to measure the ovarian cancer biomarker HE4/CRE ratio in urine.

Ovarian cancer has a poor cure rate and rates of relapse are high. Current recurrence detection is limited by non-specific methods such as blood testing and ultrasound. Based on reports that human epididymis four (HE4) / creatinine (CRE) ratios found in urine are elevated in ovarian cancers, we have developed a paper-based device that combines lateral flow technology and cell phone analysis to quantitatively measure HE4/CRE. Surrogate samples were used to test the performance over clinically expected HE4/CRE ratios. For HE4/CRE ratios of 2 to 47, the percent error was found to be 16.0% on average whether measured by a flatbed scanner or cell phone. There was not a significant difference between the results from the cell phone or scanner. Based on published studies, error in this method was less than the difference required to detect recurrence. This promising new tool, with further development, could be used at home or in low-resource settings to provide timely detection of ovarian cancer recurrence.

Low-Cost, Volume-Controlled Dipstick Urinalysis for Home-Testing.

Dipstick urinalysis provides quick and affordable estimations of multiple physiological conditions but requires good technique and training to use accurately. Manual performance of dipstick urinalysis relies on good human color vision, proper lighting control, and error-prone, time-sensitive comparisons to chart colors. By automating the key steps in the dipstick urinalysis test, potential sources of error can be eliminated, allowing self-testing at home. We describe the steps necessary to create a customizable device to perform automated urinalysis testing in any environment. The device is cheap to manufacture and simple to assemble. We describe the key steps involved in customizing it for the dipstick of choice and for customizing a mobile phone app to analyze the results. We demonstrate its use to perform urinalysis and discuss the critical measurements and fabrication steps necessary to ensure robust operation. We then compare the proposed method to the dip-and-wipe method, the gold standard technique for dipstick urinalysis.

Smartphone-based optical spectroscopic platforms for biomedical applications: a review [Invited].

Rapid advancements in smartphone technology have enabled the integration of many optical detection techniques that leverage the embedded functional components and software platform of these sophisticated devices. Over the past few years, several research groups have developed high-resolution smartphone-based optical spectroscopic platforms and demonstrated their usability in different biomedical applications. Such platforms provide unprecedented opportunity to develop point-of-care diagnostics systems, especially for resource-constrained environments. In this review, we discuss the development of smartphone systems for optical spectroscopy and highlight current challenges and potential solutions to improve the scope for their future adaptability.

Recent trends in smartphone-based detection for biomedical applications: a review.

Smartphone-based imaging devices (SIDs) have shown to be versatile and have a wide range of biomedical applications. With the increasing demand for high-quality medical services, technological interventions such as portable devices that can be used in remote and resource-less conditions and have an impact on quantity and quality of care. Additionally, smartphone-based devices have shown their application in the field of teleimaging, food technology, education, etc. Depending on the application and imaging capability required, the optical arrangement of the SID varies which enables them to be used in multiple setups like bright-field, fluorescence, dark-field, and multiple arrays with certain changes in their optics and illumination. This comprehensive review discusses the numerous applications and development of SIDs towards histopathological examination, detection of bacteria and viruses, food technology, and routine diagnosis. Smartphone-based devices are complemented with deep learning methods to further increase the efficiency of the devices. Graphical Abstract.

Low-Cost, Robust, and Field Portable Smartphone Platform Photometric Sensor for Fluoride Level Detection in Drinking Water.

Groundwater is the major source of drinking water for people living in rural areas of India. Pollutants such as fluoride in groundwater may be present in much higher concentration than the permissible limit. Fluoride does not give any visible coloration to water, and hence, no effort is made to remove or reduce the concentration of this chemical present in drinking water. This may lead to a serious health hazard for those people taking groundwater as their primary source of drinking water. Sophisticated laboratory grade tools such as ion selective electrodes (ISE) and portable spectrophotometers are commercially available for in-field detection of fluoride level in drinking water. However, such tools are generally expensive and require expertise to handle. In this paper, we demonstrate the working of a low cost, robust, and field portable smartphone platform fluoride sensor that can detect and analyze fluoride concentration level in drinking water. For development of the proposed sensor, we utilize the ambient light sensor (ALS) of the smartphone as light intensity detector and its LED flash light as an optical source. An android application "FSense" has been developed which can detect and analyze the fluoride concentration level in water samples. The custom developed application can be used for sharing of in-field sensing data from any remote location to the central water quality monitoring station. We envision that the proposed sensing technique could be useful for initiating a fluoride removal program undertaken by governmental and nongovernmental organizations here in India.

Smartphone-based platform optical setup measuring π/256 optical phase difference in an interference process.

Utilizing the camera of a smartphone and simple laboratory optical components, we demonstrate an optical technique that measures an optical phase difference (OPD) of π/256 in an interference process. We develop a compact optical setup for viewing circular interference fringe patterns through the camera of the smartphone. By introducing OPD between the interfering beams, variation in fringe pattern is recorded using the smartphone camera. We envision that the proposed optical setup could emerge as an ultrasensitive optical tool for measurement of inclination of a given surface.